Diabetes mellitus is a lifelong incapacitating disease with worldwide prevalence estimated at 150 million patients in 2000. Loss of sufficient insulin production by the pancreatic beta-cell is a hallmark of both type 1 and type 2 diabetes. The development of allogenic islet transplantation using steroid-sparing immunosuppression has raised new hope for better treatment of severe diabetes. However, the experience at multiple clinical centers over the past 4 years has shown that transplant outcome is highly variable, with insulin-independence ranging from 30% to 80% 1 year after transplant. We propose to systematically evaluate the quality of human pancreatic islets as a potentially crucial factor in transplant outcome utilizing both biochemical as well as functional genomics approaches, with the ultimate goal of developing a rapid, economic and reproducible assay of islet quality that correlates with the outcome of the transplant. We will pursue this goal in two specific aims: First, we will determine the expression profile of human islet preparations procured at the University of Pennsylvania using the human PancChip cDNA array developed in the Kaestner lab. In addition, we will measure glucose stimulated insulin secretion using islet perifusion, and evaluate islet function in vivo using minimal islet mass transplantation into diabetic NOD-Scid mice. We will then correlate the expression profile data with the in vitro and in vivo islet function tests, to determine which set of genes is most predictive of highly functional islets. Furthermore, we will investigate whether any of the 3 parameters determined in the lab correlate with clinical outcome as determined by following the decrease of insulin requirement in the transplant recipients. Second, we will apply discriminant analysis to the microarray data to identify a set of up to 96 genes that are most predictive of islet function. We will use this information to develop a TaqMan low density array that will allow for the rapid determination of the corresponding mRNA levels using real time PCR. We will test this "Array-by-Design" as a predictive tool of islet quality and function using the metrics described in Aim1. If successful, this rapid screen could be incorporated as a quality control step for human islets before transplant, and in addition as a cost-effective tool to evaluate beta-cells derived from other sources such as adult stem cells or hepatocytes.